u n i ve r s i t y o f co pe n h ag e n

Expert consultation workshop on transboundary effects

D7.3

Yu, Wusheng; Clora, Francesco; Rankovi, Ana; Kelly, Garret Patrick

Publication date:2019

Document versionPublisher's PDF, also known as Version of record

Citation for published version (APA):Yu, W., Clora, F., Rankovi, A., & Kelly, G. P. (2019). Expert consultation workshop on transboundary effects:D7.3. EUCALC.

Download date: 12. jun.. 2021

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730459.

Expert consultation workshop on

transboundary effects

_________

D7.3

04/2019

Ref. Ares(2019)4178903 - 02/07/2019

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Project Acronym and Name

EU Calculator: trade-offs and pathways towards sustainable and low-carbon European Societies - EUCalc

Grant Agreement Number

730459

Document Type Report

Work Package 7

Document Title Expert consultation workshops on transboundary effects

Main authors Wusheng Yu, Francesco Clora (UCPH)

Ana Ranković, Garret Patrick Kelly (SEECN)

Partner in charge UCPH

Contributing partners SEECN, BPIE, TUDelft, Imperial College London

Release date 24/04/2019

Distribution Public:

All involved authors and co-authors agreed on the

publication.

Short Description

This deliverable describes presentations, discussions and lessons learnt during the EU Calculator Expert consultation workshop on transboundary effects, held

on the 22nd of November, 2018. The three main topics of discussions were the representative scenarios to be formulated and simulated in the transboundary

effect module, the exploitation of the trade results in the Pathway Explorer, and CGE implications of the macro-level development of trade and globalization.

Quality check

Name of reviewer Date

Boris Thurm (EPFL) 30/04/2019

Statement of originality:

This deliverable contains original unpublished work except where clearly indicated

otherwise. Acknowledgment of previously published material and of the work of others

has been made through appropriate citation, quotation or both.

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EUCalc policy of personal data protection in regard to the workshop EUCalc defined the procedures in order to reply to ethical requirements in Deliverable 12.1

(Ethics requirements – procedures and criteria to identify research participants in EUCalc

– H – Requirements No. 1). All procedures in relation to the co-design process, in particular

the stakeholder mapping, the implementation of the workshops and the follow-up of the

workshops, follow these procedures. The informed consent procedure in relation to the

workshops is based on D9.2 “Stakeholder mapping” and D9.4 “Method for implementation

of EUCalc co-design process”. The originals of the signed consent forms are stored at the

coordinators’ premises without possibility of access of externals. Scans of the informed

consent forms are stored on the internal EUCalc file storing system.

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Table of Contents

EUCalc policy of personal data protection in regard to the workshop ...... 3

Glossary .................................................................................................. 5

1 Executive summary ............................................................................ 6

2 Introduction ....................................................................................... 8 2.1 Objectives of the expert consultation .................................................... 9

3 Workshop description ...................................................................... 10 3.1 Setting the scene ............................................................................. 10 3.2 Description of the transboundary module of the European Calculator ...... 10

3.2.1 Modelling approach .................................................................. 10 3.3 Discussion & recommendations .......................................................... 11

3.3.1 Relevant and representative user-defined pathways in the EUCalc for generating the transboundary effects .................................................... 12 3.3.2 Presentation of the transboundary effects in EUCalc ..................... 13 3.3.3 Modeling assumptions .............................................................. 14

4 Lessons and conclusions .................................................................. 18

5 References ....................................................................................... 20

6 Annexes ........................................................................................... 23 6.1 Participants list ................................................................................ 23 6.2 Workshop agenda ............................................................................. 24 6.3 Dialogues’ sheet ............................................................................... 25

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Glossary

BAU: Business As Usual

CGE: Computable General Equilibrium

EU: European Union

GDP: Gross Domestic Product

GHG: Greenhouse Gas

GTAP: Global Trade Analysis Project

MS: Member State

ROW: Rest Of the World

SSP: Shared Socio-economic Pathway

TFP: Total Factor Productivity

UCPH: University Of Copenhagen

WP: Work Package

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1 Executive summary The representation of transboundary effects within the EUCalc was discussed at an expert

engagement workshop held in Brussels on 22nd November 2018. The workshop was

attended by the EUCalc team responsible for the transboundary module and experts from

a range of institutions representing the views of both governmental and non-governmental

research and policy organizations.

The workshop started with a series of presentations by the EUCalc team. Professor Jeremy

Woods from Imperial College London (ICL) and Ana Rankovic from SEE Change Net gave

introductory presentations on the logic of the project and the concept of the EUCalc model.

Professor Wusheng Yu from University of Copenhagen presented the results of the

preliminary research activities under the transboundary module, as well as associated

challenges, to participating experts. This introduction was then followed by three discussion

sessions focusing respectively on three sets of questions prepared by the EUCalc team. In

these sessions, the experts were invited to provide their insights, suggestions and

comments to help shaping the modeling approach and overcome modeling challenges.

In general, the workshop participants recognize the uniqueness of the EUCalc modeling

approach and its potential contributions to the EU decarbonization debates. The major

challenges associated with modeling the transboundary effects among the European Union

Member States (EU MS)and between the EU and the rest of the world (ROW) using

"bottom-up" inputs from the rest of the EUCalc model, as presented at the workshop, are

clearly understood by the participants. The discussions confirmed the complex nature of

the modeling choices that the EUCalc team will have to make in the modeling work. The

experts were supportive of the modeling approach proposed by the EUCalc team while

offering many insightful suggestions for tackling the modeling challenges identified.

More specifically, on the questions concerning representative scenarios to be formulated

and simulated in the transboundary effect module, the experts agree with the team's

general approach to only select and model relevant and representative EUCalc pathways.

On the three sets of scenarios that we proposed in the pre-reading material and presented

at the workshop, the experts emphasized the need to pay attention to the scenarios that

are likely to be used by users. One suggestion is to aggregate along the member state

dimension and focus more on sectoral decarbonization differences. This effectively further

reduces the number of scenarios to be modeled. Another suggestion is to model an even

smaller set of scenarios and list them as pre-defined pathways in the EUCalc pathway

explorer. In general, the experts cautioned against the ambition to model too many

scenarios in a complex CGE model. The idea of using the selected representative scenarios

to "envelope" or represent the full set of EUCalc pathways are supported by the

participants; however, the experts were quite cautious about the necessity and the

feasibility to make "interpolations" to approximate the non-modeled scenarios.

On the questions regarding the exploitation of the results, the participants offered insightful

suggestions and recommendations. They agreed with the need to further process the

transboundary results into key indicators to facilitate the display of such results. Among

the suggested indicators are the ones that can be derived from the modeling results, such

as changes in trade balances and carbon leakages through trade by country and at EU

level, and possibly with further breakdowns by key sectors. Other suggested indicators

were also mentioned, such as air pollutants and labor market related issues, which are out

of the scope of the transboundary module but are dealt with in other EUCalc modules.

Moreover, suggestions were also provided on allowing users to dig deeper into the results.

The last set of the questions deals with both the macro level development of trade and

globalization and the underlying modeling instruments of these macro trends, as reflected

in the design of the baseline and the selected scenarios. Here, there is a broad support for

the baseline compilation and implementation approach documented in D7.1. On the

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specific modeling issues that we brought for discussion at the workshop (e.g. long term

trade policy trends, trade to GDP ratio, size of trade elasticities, sectoral productivity

growth, fossil fuels prices, and land supply), it appears that modelers generally agree to a

set of "best practices" (which are in fact being used by the EUCalc team) but they indicated

that the exact model implementations do differ across models and modeling teams. In any

case, the specific suggestions gathered in this session pointed us to additional data,

parameters and assumptions that can either be used or cited as further references in the

modeling work.

Overall, this workshop was an important milestone in the research and design of the

transboundary module. The experts' inputs are being assessed and used for the

improvement of the EUCalc tool. The project will continue to interact with the experts,

those who attended the workshop as well as those who, although unable to attend the

workshop, expressed their interest to be involved.

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2 Introduction With the aim of providing decision makers with accessible climate and energy modelling

solutions, the EUCalc project will create a state-of-the-art model for analyzing trade-offs

and pathways towards a sustainable and low-carbon European future. An associated web-

tool, the Transition Pathways Explorer, will provide instant results from the European

Calculator model runs and allow users to explore options for reducing GHG emissions from

now to 2050, as well as to see the consequences of these choices on multiple sustainability

issues in real-time.

The EUCalc addresses multi-dimensional and inter-disciplinary issues that requires a wide

range of expertise to develop the tool. In this context, the EUCalc embeds a co-design

process with stakeholders who are leading experts in their field. The co-design process is

organized through a series of workshops, one for each main module (see Figure 1).

Through this approach, external experts are part of the designing process which enables

them to shape and calibrate the EUCalc tool by helping co-design the determinants and

the scope of the scenarios.

Fig. 1 Modular structure of the European Calculator Model

The University of Copenhagen (UCPH) is leading the work package on “Transboundary

Effects and Trade flows” ("WP7" hereafter) of the EUCalc project, in collaboration with PIK-

Potsdam, Imperial College London, Climact, Climate Media Factory, T6ECO, SEE Change

Net and TU Delft.

Within the broader scope of the Calculator, the WP7 aims at quantifying the transboundary

effects on intra- and extra-EU trade flows of alternative EUCalc pathways by using a

computable general equilibrium (CGE) modelling framework. The simulated transboundary

effects will inform EUCalc users of likely future economic dependencies inside the EU as

well as between the EU and the rest of the world due to the EU's decarbonization efforts.

The EUCalc expert engagement workshop devoted to "Transboundary effects of EU

decarbonization pathways" was held in Brussels, at the European Climate Foundation, on

22nd November 2018.

The UCPH team identified beforehand several challenges that have surfaced during the

research and design phase of the transboundary module. In order to facilitate the workshop

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deliberations, a pre-reading document was provided to participants in advance, including

preliminary research results and information about modelling approach and methodology

(Section 3.2).

Ten experts from international organizations, public and private sector with relevant expert

background and experience to critic as well as to provide evidence-based input regarding

the transboundary effects and trade flows on both European and global scale, attended

and contributed to the workshop discussions. Participants list is annexed to this report

(Section 6.1)

The workshop was professionally designed and facilitated. It was composed of the three

distinct components:

• Introduction of the EUCalc project in a plenary scene setting (Section 3.1);

• Presentation of the specific components of the Transboundary module (Section

3.2);

• Break-out group discussions in which experts reviewed and reported back on

key questions and topics (Section 3.3).

2.1 Objectives of the expert consultation

The "Transboundary effects of EU decarbonization pathways" workshop introduced the

philosophy of the EUCalc tool to a cross-section of experts. It also presented preliminary

research results and assumptions of the EUCalc's transboundary module. The workshop

provided a venue for experts to critically examine, validate and advise on the underlying

methodology.

Participants were invited to work in small groups and to collect their thoughts individually

and collectively on each of the following discussion areas that constitute some of the

challenges faced by WP7 in the modelling work:

The most relevant and representative EUCalc user-defined pathways to be

simulated in a CGE model for generating the transboundary effects, including the

sets of potential scenarios proposed by the EUCalc team and/or any other

important/relevant scenarios.

The ways to present transboundary effects in the EUCalc (e.g. as the trade matrix

itself or in terms of key indicators) including the question of what key transboundary

effects, at what sectoral aggregation level and how they should be presented in

EUCalc

The long-run relationship between GDP growth and trade expansion, the size of key

parameters such as trade elasticities (e.g. Armington elasticities), the use of

differential sectoral productivity growth pattern to generate expected structural

changes, the treatment of land and other natural resource supply, and the

representation of changing energy technologies in a trade-focused CGE model.

These questions can be more generally summarized in a discussion on recent

setbacks in globalization and global cooperation, their implications on long run trade

development and decarbonization efforts, as well as the EU's future position and

role in global trade and global decarbonization efforts.

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3 Workshop description

3.1 Setting the scene

The expert consultation workshop was opened with a welcome speech given by Professor

Wusheng Yu from the University of Copenhagen, the institution organizing the workshop.

Professor Jeremy Woods from the Imperial College London gave an overview presentation

on the EUCalc project. He outlined the history, philosophy and the logic of the Calculator's

approach. By using the Global Calculator as a proxy, he demonstrated how it allows users,

particularly decision makers, to interactively navigate, use and visualize the results of each

selected scenario. He was then followed by Ana Rankovic from SEE Change Net, who

highlighted the role and importance of the co-design process for the EUCalc development.

Their introductory presentations were followed by an overview of the transboundary

module.

3.2 Description of the transboundary module of

the European Calculator

In his introductory presentation, Professor Wusheng Yu focused on the specific features of

the transboundary module (e.g. modelling approach, scope etc.), while also highlighting

several challenges that have surfaced during the design phase of the module.

Within the EUCalc project, transboundary flows refer to the trade of goods and services

amongst the EU MS, as well as between the EU and the Rest of the World (ROW). As the

envisioned decarbonization pathways impose changes in both demand and supply for a

number of sectors (e.g. energy, materials, food, transport), levels and structures of

production and consumptions at sectoral and country levels would also be altered. This in

turn would change the internal and external economic dependences concerning the EU MS

at sectoral levels and lead to changed trade patterns. Furthermore, as transboundary flows

of goods and services embody energy consumption and GHG emissions, projecting

transboundary flows is therefore an important consideration in evaluating the options and

tradeoffs of EU decarbonization pathways.

3.2.1 Modelling approach

Modeling the transboundary effects mandates the use of an economic modeling system

that takes into consideration not only inter-sectoral linkages such as the input-output

linkages connecting raw materials and fossil fuels to final outputs, but also linkages through

the competition/allocation of available economic resources such as labor and capital.

Further, EU MS and the rest of the world must also be connected in the model such that

imbalances between demand and supply at sectoral levels for each country can be

accounted for via transboundary trade flows. Essentially, this points to the use of a global

computable general equilibrium (CGE) model focused on trade linkages. In fact, CGE

models are a typical tool for empirical analysis of distributional and welfare impact of

different policies (Wing, 2004, Burfisher, 2011). More generally, they can be used to

measure the result of shocks to an economic system (i.e. computable), encompassing

simultaneously all economic activities (consumption, production, employment, taxes,

savings, trade etc.) and the linkages among them (i.e. general), in an economy where at

a given set of prices all agents are satisfied (i.e. equilibrium) (Burfisher, 2011). To analyze

the trade and transboundary effects of EUCalc decarbonization pathways, WP7 adopts a

modified version of the GTAP-E model (Burniaux and Truong, 2002, McDougall and Golub,

2007), which is the energy-environmental version of the GTAP model (Hertel et al., 1997).

The GTAP model is generally considered as a standard CGE model. GTAP’s expansive

country coverage and its general equilibrium modelling structure on sectoral and trade

linkages within and across countries complement the scope of the EUCalc as it allows for

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simulating the transboundary effects of alternative EUCalc pathways under various lever

settings.

Substantive research efforts in WP7 include:

Constructing baseline projections based on the GTAP9 database (Aguiar et al.,

2016) at its sectoral and country classifications to 2050, to coincide with the 2050

timeline envisioned in other WPs of the EUCalc;

Modifying the structure of the GTAP-E core model to accommodate the sectoral

coverages of other EUCalc WPs, including sectoral energy consumption and

emissions;

Designing an interface to facilitate the transformation of alternative sectoral EUCalc

pathways as inputs into the specifically designed GTAP model for simulating the

transboundary effects;

And simulating the alternative EUCalc pathways as model scenarios to generate the

transboundary effects to be included in the EUCalc pathway explorer.

Thus, this WP interacts with WPs 1-5 by using their results and with WP8 by supplying the

transboundary effects as inputs.

3.3 Discussion & recommendations

The third and largest segment of the workshop was dedicated to eliciting input from

experts.

In particular, the discussion focused mainly on the three following questions:

Representative scenarios: What are the most important, relevant and

representative user-defined EUCalc pathways to be simulated in the CGE model for

generating the transboundary effects, particularly concerning the commonalities

and deviations of decarbonization ambition levels across member states and

sectors? Once selected, these representative scenarios will be used to form an

"envelope" to approximate the full range of the virtually unlimited EUCalc user-

defined decarbonization pathways.

Key transboundary effects: What key transboundary effects (e.g. intra and extra-

EU trade flows) should the model exercises focus on? At what sectoral aggregation

level and for which key sectors should such results be computed? How should the

simulated transboundary effects be presented in EUCalc (e.g. as the trade matrix

itself or in terms of key indicators such as self-sufficiency ratio, trade

dependency/exposure index, or other indicators)?

Modelling assumptions: Is there a long-run relationship between GDP growth and

trade expansion and, if so, how can such relationship be enforced in the CGE model?

What is the "correct" range of key parameters such as trade elasticities (e.g.

Armington elasticities)? In simulating scenarios of large structure changes, what

are the reasonable assumptions regarding differential sectoral productivity growth

patterns? In a trade-focused CGE model, how should long-run land and other

natural resource supply be specified? And how can changing energy technologies

be parsimoniously represented?

During the workshop, handouts and guiding questions were provided to help start the

discussions (Section 6.3). The workshop also engaged the assistance of designated

rapporteurs made up of members of the consortium.

The experts' inputs and suggestions in each discussion area are presented hereinafter.

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3.3.1 Relevant and representative user-defined pathways in the EUCalc for generating the transboundary effects

EUCalc will generate billions of “instant” results, given the very large possibilities of

combining its levers. This is not possible in GTAP, which requires precise calibration of the

modifications to be imposed in the model and time to simulate the scenarios1. Owing to

the size and computational complexities of the CGE model to be used, the trade module

will focus on simulating the transboundary effects of a subset of the virtually unlimited

user-defined decarbonization pathways to provide an "envelope" to approximate the full

set of user-defined pathways.

Deliverable 7.2 (Baudry et al., 2018) lists potential scenarios to be simulated in GTAP.

They can be divided into three categories:

The first set will simulate scenarios with identical ambition levels in all sectors and

countries (i.e. 4 scenarios deriving from the 4 lever settings);

The second set will simulate different ambitions across the sectors, with sectoral

ambition levels being kept the same across EU MS;

The third set simulates scenarios with deviations by individual countries from the

EU-wide ambition, i.e. each EU MS is assumed to deviate its level settings (uniform

across sectors) from the common level setting assumed for all other MS in the core

scenario.

It is possible that not all of these scenarios can be successfully computed, mainly because

some particular pathways (e.g. those linked to ambition levels set at 3 or 4, i.e. very high

ambitions) may represent a drastic departure from the current state of the economic

system, for which the CGE model may not be able to find equilibrium solutions. The sectoral

and regional aggregations play a fundamental role in obtaining coherent and reliable

results from GTAP. For some small MS, the production and trade matrices in the GTAP

database present values that are very close to zero. This increases drastically the risk of

incurring in corner solutions, hindering the accuracy or even the solvability of the model.

Therefore, the experts suggested to show a warning sign in the Transition Pathway Explorer

whenever an user-defined EUCalc pathway cannot be simulated in GTAP.

The experts clearly understood these challenges and generally supported the pragmatic

modeling approach presented at the workshop. They highlighted the trade-off between

modeling the EU as a whole while at the same time increasing the sectoral granularity and

modelling individual EU member states with a denser sectoral aggregation in the CGE

model. An intermediate alternative was also proposed by some of the experts to aggregate

some of the EU MS with either similar economic structures (e.g. Benelux, Baltic countries)

or whose trade matrices are “too small” to be specifically modelled in the EUCalc context

(e.g. Malta, Cyprus). The proposal to focus the modeling exercise on the sectoral

differences (at an aggregated EU level) rather than at the individual MS level suggests to

focus on the first and second sets of the proposed scenarios outlined above, rather than

the third set where countries individually deviate from the EU-wide pathways.

Regarding the ambition in simulating 600+ scenarios in the CGE model, a number of

potential complexities were raised by the modelers. In particular, modeling in GTAP

technological breakthroughs (i.e. level settings 4, corresponding to the highest abatement

ambition) can be challenging and misleading, as it implies major ‘unforeseeable’ changes

in a sector having a spillover effect on the rest of the economy, and leading to major abrupt

structural changes that are potentially inconsistent with the current economic structure.

The “envelope” approach to use a limited set of representative, important and relevant

scenarios to represent the full set of possible EUCalc pathways was widely supported by

1 Depending on the sectoral and regional aggregation and on a set of other parameters, it

can take up to hours to compute a solution in GTAP

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the modelers attending the workshop, as it offers the best balance between plausibility

and exploring boundary conditions, in terms of ambitions and sectors involved. In fact,

rather than computing all or most of the selected scenarios listed above to form an

envelope for the full set of EUCalc pathways, some participants even proposed to only

model a much smaller number of relevant ones and show them to the final EUCalc user as

pre-defined pathways, in a fashion similar to the Global Calculator. These pre-defined

pathways could be the EU's or individual countries’ NDC targets and other relevant climate

scenarios that are likely to be of interest to the users (however, the experts did not specify

these other scenarios.

Two other suggestions not included in the proposed sets of scenarios were offered:

- The addition of scenarios measuring how different climate ambitions in ROW affect

the carbon leakages of different EUCalc pathways;

- A “policy comparison” within the CGE model, where different instruments (e.g.

carbon tax, cap and trade or “twist parameter”(Dixon and Rimmer, 2002)) are used

to achieve the same pathways.

Both suggestions are highly relevant in the current current academic and political debates.

However, the current scope of the EUCalc project prevent us from pursuing these

suggestions.

3.3.2 Presentation of the transboundary effects in EUCalc

A single simulation in GTAP generates a substantial amount of trade-related results which,

if not properly presented to the model users, may be difficult to read and use. This would

hamper one of the objectives of EUCalc (i.e. accessibility) and would deprive EUCalc of one

of its distinctive features from the existing family of Calculators, i.e. computing trade

effects arising from different EU decarbonization pathways. Therefore, a practical way to

effectively exploit the results derived from GTAP is to further process the results to obtain

some indicators that may be meaningful for users and policymakers and are easy to

present in the online EUCalc Pathway Explorer.

Acknowledging this, the experts were asked what key transboundary effects (e.g. intra and

extra-EU trade flows) should the WP7 focus on, at what sectoral aggregation level and for

which key sectors should such results be accessible, and how should the transboundary

effects be presented in EUCalc (e.g. as the trade matrix itself or in terms of key indicators

such as self-sufficiency ratio, trade dependency/exposure index, revealed comparative

advantage index, etc.).

The identified key transboundary effects are the changes in the trade balances, both in

monetary values and embedded GHG emissions. More precisely, the analysis of self-

sufficiency in strategic sectors (e.g. emission-intensive sectors, food, fuels, materials, etc.)

has been recognized as crucial, together with the accounting of the GHG content of the

commodities traded.

Carbon leakage both inside and outside the EU has been suggested as a highly relevant

issue. In order to achieve additional accuracy in observing whether a country is a net

importer or net exporter of embodied emissions, it has been suggested to divide the ROW

region into a few regions (e.g. USA, China, India, Japan, high income countries, low income

countries). Aside from these suggestions, several experts also expressed wishes for

additional results in the trade module, such as energy- and water-intensive commodities

and even biodiversity, even though the experts considered this highly challenging for the

timeframe of the EUCalc project. Some experts also mentioned labor market issues such

as labor mobility and migration, issues are potentially related to the employment module

of EUCalc.

The sectoral granularity, according to some participants, would ideally be at the lever level.

However, according to most of the other contributors, this could be misleading for the user

and is virtually impossible to model in detail in the CGE. The focus could then be on the

sectors grouped according their emission intensities (sensible for presenting and

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highlighting the carbon leakages) and/or on sectors used in other climate-related modelling

exercises (e.g. IPCC classification) and/or sectors as separated in policy decisions (NDC

sectors, or ETS vs non-ETS sectors). A “magnifying glass” approach (i.e. providing

interactive menus on the pathway explorer to allow users to dig deeper into the results)

has been proposed by some experts, as it provides the user with both an overview on the

main EUCalc sectors, at the same time allowing for analyzing more in detail each of the

sectors.

Additionally to the transboundary flows both in monetary and GHG terms, a number of

other proposals were presented, from ‘simple’ indexes as the net trade position intra- and

extra-EU or emission shares to the less intuitive KAYA identity (Kaya and Yokoburi, 1997).

Other inputs have been given in terms of the graphs to show, with a relatively general

agreement on using maps at the regional level. It has also been proposed to offer a “bulk

download” possibility (e.g. a .csv file) to allow the users to carry out their own calculation

from the “raw” GTAP results. Finally, it was stressed that representation of uncertainty is

of utmost importance and some sensitivity analysis of the key GTAP parameters could help

in achieving this representation. However, given the large number of simulations to

conduct, it is impractical to conduct sensitivity analysis for these simulations.

3.3.3 Modeling assumptions

Part of the efforts in WP7 are towards the construction of a baseline based on the GTAP9

database, as mentioned in section 3.2.

The purpose of the baseline construction is to establish a likely business-as-usual (BAU)

scenario towards 2050, against which the transboundary effects of alternative EU

decarbonization pathways can be simulated. In Deliverable 7.1 (Yu and Clora, 2018), we

gathered annual GDP projections and the associated main drivers such as population, labor

force (skilled and unskilled), capital stock, and total factor productivities for individual

countries including all EU MS. After surveying several recent model-based projections that

can be considered as BAU, i.e. various "reference” scenarios and Shared Socioeconomic

Pathway 2 (SSP2)2 projections, we selected the following sources:

- GDP: EU Reference Scenario 2016 (European Commission et al., 2016) and OECD-

SSP2 (Dellink et al., 2017);

- Population: EUROSTAT, EU 2015 Ageing Report (European Commission (DG ECFIN)

and Economic Policy Committee (AWG), 2014, European Commission (DG ECFIN)

and Economic Policy Committee (AWG), 2015) and SSP2 projections for IIASA (Kc

and Lutz, 2017);

- Labor force: EUROSTAT, EconMap2.4 (Fouré and Fontagné, 2016) and EU 2015

Ageing Report (European Commission (DG ECFIN) and Economic Policy Committee

(AWG), 2015). Total labor force is divided into skilled and unskilled, drawing from

education projections obtained from Fouré and Fontagné (2016), which in turn are

gathered from Kc and Lutz (2017);

- Capital stock: EconMap2.4 (Fouré and Fontagné, 2016);

- Total factor productivity (TFP): EconMap2.4 (Fouré and Fontagné, 2016) and EU

2015 Ageing Report (European Commission (DG ECFIN) and Economic Policy

Committee (AWG), 2015).

With these data, we used the GTAP-E model to project the world economy from 2011,

which is the base year of the GTAP-E 9 database (Aguiar et al., 2016), to 2050. In this

projection, we targeted population and labor force projections during the 2011-2050 period

2 The Shared Socioeconomic Pathways describe alternative trends in the evolution of society and ecosystems from 2005 to 2100 at the world and regional levels. The SSPs are part of a framework

that the climate change research community has adopted to facilitate the analysis of future climate

impacts, vulnerabilities, adaptation, and mitigation. In SSP2, the world would undergo a transformation in which social, technological and economic trends do not deviate much from historical patterns observed over the past century.

D7.3

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by directly imposing shocks to the correspondent exogenous GTAP variables. To project

GDP, we endogenized TFP in order to target the projected GDP levels. Additionally, we

endogenized the total capital stock using the “Baldwin equation” (Francois and McDonald,

1996), opting for a fixed savings rate closure with capital accumulation.

In addition to implementing the macroeconomic projections, we also targeted the projected

changes in fossil fuel prices (IEA, 2012, IEA, 2017) by endogenizing changes in the

productivity of the oil, coal and gas sectors. Finally, we also assumed a 2 percentage points

differential with respect to the regional TFP between the manufacturing sectors and other

sectors.

When implementing the baseline, it is obvious that many other factors may also shape the

world economy and the way the world economy is interconnected in the long term. For

instance, different CGE modelling groups apply different approaches with respect to

sectoral productivity differentials, trade openness and trade costs, aggregate land and

natural resource supply, long-term income elasticities, and linkages between the economy

and the environment. All these considerations may have non-trivial implications on the

structure of the projected baseline.

With respect to inter-sectoral productivity differences, we followed an approach similar to

the one suggested in Fouré and Fontagné (2018) and LINKAGE (Van der Mensbrugghe,

2005). The two studies assume 2 percentage points additional productivity change in

manufacturing with respect to services and use exogenously defined TFP for agriculture.

In our projection exercise, we assumed the manufacturing sectors' TFP to be 2 percentage

points higher than the average regional TFP. Other studies, such as the WTO World Trade

Report 2018 (WTO, 2018a), estimate econometrically these productivity differentials with

respect to the average TFP in each region, based on databases such as EU KLEMS and

OECD-STAN. There are also a few CGE models that use an array of differential sectoral

productivities, in particular with respect to the relative TFP growth in agriculture. For

example, Robinson et al. (2014) suggest that TFP growth in both developed and developing

countries is highest in agriculture, followed by manufacturing and services.

In addition to inter-sectoral productivity differences, other major drivers of structural

change are trends/assumptions on trade policies and globalization and trade-related

parameters.

In long-run projections, current or historical trade policy trends are typically assumed. For

example, Fouré and Fontagné (2018) adjust tariffs to their historical trend (2004-2011),

using MacMap HS-6 CEPII ITC database. Given the recent setbacks in globalization and

global cooperation, one may wonder whether there will be a need to modify our recent

assumptions on trade policy trends or whether the recent setbacks are merely a transitory

phenomenon that would not be persistent in the period of our projection.

Another important issue in long run projection of trade flows rests on the size of the trade

elasticities. Thus far, we have been using the Armington elasticities3 provided in the GTAP-

E 9 database. However, given the major structural changes in the world economy, the

estimation of correct Armington elasticities is crucial, as the standard ones could lead to

unreasonable trade volumes for certain products among regions (Schuerenberg-Frosch,

2015). For example, if a sector-specific carbon tax is implemented, the high elasticity for

gas could result in over-traded gas as it has lower emission intensities as compared to

other fossil fuels (oil and coal). On the other hand, as EU countries are operating within an

integrated market, the opposite argument for higher elasticities for intra-EU trade flows of

many other products may be appropriate. Therefore, guidance on adopting appropriate

trade elasticities was needed.

3Armington elasticity: elasticity of substitution between imported products sourced from different

exporting countries. It is based on the assumption made by Paul Armington in 1969 that products traded internationally are differentiated by countries of origin. Therefore, it governs the strength of the relative demand responses to relative international prices.

D7.3

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The assumptions regarding the trade-to-income elasticity are also essential for determining

the aggregated global trade volume in 2050. Fouré and Fontagné (2018) calibrate the

trade-to-income elasticity on historical data. However, this elasticity has been falling in

recent years relative to its long-run trend (Hukkinen et al., 2016). Since carbon leakages

are crucial within the EUCalc, the decision of exogenizing or endogenizing the trade-to-

income ratio is of fundamental importance, as it will have a major impact on the final

results. In some CGE models, the base assumption is a linear relationship between GDP

growth and trade expansion, which nevertheless does not fit well with past observations

(WTO, 2018b).

Moreover, reductions in trade costs are an important factor to take into account, in

particular in the light of the importance of trade for the EUCalc. In the last decades, falling

trade costs have been observed (OECD and WTO, 2015). Furthermore, the adoption of

new transportation technologies and the opening of the Northern Sea Route due to melting

ice caps may further reduce transportation costs in the future (Bekkers et al., 2018). Thus,

whether or not efficiency gains in the global transportation sectors should be considered

becomes a relevant question.

An additional issue, connected to the expected increase in food demand towards 2050, is

about the long-run supply of aggregated land. Currently, in GTAP total land supply is fixed

at the regional level. However, rising land rents may cause additional land to be brought

under cultivation, even though the price elasticity of land supply is estimated to be very

low (Renwick et al., 2013, Philippidis et al., 2017). The finite amount of land (and the

impossibility of “producing an extra unit”) may be solved by introducing a logistic function

for land supply in GTAP, as e.g. in ENVISAGE v104(van der Mensbrugghe, 2018).

Given the multifaceted complexities of such discussions, the participants were divided in

two groups looking into them from different angles. The first group focused on the general

macro-trends, whereas the second focused on how these trends should be approached

from a CGE model perspective.

3.3.3.1 Macro-trends

The core of this dialogue was formed by the envisioned future trade patterns, from a wide

political-economic perspective, rather than the CGE modeling viewpoint presented in

section 3.3.3.2. In particular, trade policy trends and the role of the EU in global trade and

global decarbonization efforts were discussed.

Most of the opinions pointed out that, even though we are currently experiencing

hindrances in globalization and global cooperation, the EU position has always been prone

to support open trade policies. A stronger EU Single Market also means a stronger EU,

which in turn is expected to lead to more cooperation not only in terms of trade but also

on other issues, e.g. shared decarbonization efforts.

The EU has already pledged to reduce its emissions by 80-95% by mid-century with respect

to the 1990 level (European Commission, 2011), a goal that is likely to be upgraded to the

net-zero emission goal (European Commission, 2008). If the rest of the world does not

follow the EU efforts, the experts could envision two futures. In the first one, a number of

“carbon tariffs” based on GHG intensities of the imported commodities could be

implemented. In the second one, the EU could push for possible changes concerning trade

agreements with other world regions. In this case, trade agreements could be used as a

leverage for pushing climate policies in trade partners and transfer climate-friendly

technologies towards emerging and developing countries.

Nevertheless, the participants also acknowledged that the impact of decarbonization efforts

and climate policy on trade policy is highly uncertain. The food and energy sectors were

used as examples in the discussion. For instance, a change in dietary patterns as part of

4 In ENVISAGE v10, the aggregate land supply curve is allowed to have one of four shapes (isoelastic, logistic, hyperbola, horizontal), as needed by the modeller.

D7.3

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decarbonization efforts, intended as a change on the demand side, might lead to a surplus

of food products with high carbon intensities that would be exported out of the EU. On the

other hand, a reduction in the use of conventional sources for the production of energy

may lead to an increase in import of energy generated by renewable resources; however,

this may also lead to imbalances in the power grid because of peak supply and other

intermittency-related issues.

3.3.3.2 Model-oriented dialogues

The group of experts in this discussion tackled the questions presented in section 3.3.3

from a CGE modelling perspective. In particular, the focus was on the selection of trade

elasticities, differential productivity growth, the trade-to-income elasticity, and the short-

run versus long-run aggregate supply functions for land and natural resources.

In principle, all the experts agreed on increasing the trade elasticities in the long run, but

no agreement was reached on the magnitude for such an enlargement. In particular, their

estimation depends heavily on the econometric approach. A number of suggestions to

choose the appropriate elasticities were proposed:

- The usage of different short-run and long-run trade elasticities;

- For several scenarios a sensitivity analysis of the Armington elasticities could be

conducted to illustrate their impact on the simulated transboundary effects;

- In the case of the European Single Market, the additional trade integration can be

mimicked either by higher trade elasticities, or as lower bilateral trade costs faced

by EU countries.

With respect to differentials in sectoral productivity growth, a number of dataset

(FAOSTAT, EU-KLEMS, OECD-STAN) and Herrendorf et al. (2014) have been mentioned as

possible sources. Estimations have been performed for CGE models (WTO, 2018a),

showing that agriculture is the sector with the highest productivity growth at the world

level. This is backed by the expected reduction in real price for food in the long-run. In

some other modeling exercises(Chepeliev et al., 2018), exogenous energy efficiency

improvements are calculated in each country proportionally to their GDP growth.

Regarding the long run relationship between GDP and trade volume, the experts suggested

not to target a specific trade-to-income ratio to allow this to be endogenously determined

in the CGE model by assumptions regarding changes in energy prices, productivities

(especially in transportation) and trade costs such as tariffs. In particular, a reduction of

trade costs by around 1% or 0.5% per year might be realistic and would help in ‘targeting’

a higher trade-income ratio.

With respect to the long-run projections of available natural resources, the experts

suggested to target fossil fuel prices rather than designing a depletion function.

Nevertheless, it was considered important to compare different price projections for coal,

gas and oil (e.g. IEA, EIA and World Bank), and their effect on the baseline projection.

On the potential aggregate land supply expansion in the long-run, differences across EU

Member States were noted by the experts. A number of countries can be considered

“unconstrained”, as the total supply of land can be increased, while other countries may

be “constrained”. In case a long-run land supply function has to be created, price

elasticities calculated by Philippidis et al. (2017) may be used as a reference. This work

makes a distinction between long-run and short-run supply elasticities. An alternative,

similar to the one proposed for fossil fuel supply, could be controlling land prices by

endogenizing productivities so as to implicitly target effective land supply. However,

disagreement on this issue was observed among the experts.

D7.3

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4 Lessons and conclusions This workshop brought together a group of active experts and stakeholders with relevant

expertise in trade and climate modeling and/or with policy advising roles in leading

research institutions and key international organizations and EU institutions. Most of the

expert participants have extensive exposures and experiences in economic/trade modeling

of climate changes. Their participation therefore greatly complements the technical

expertise within the EUCalc project consortium in providing valuable insights and

suggestions on the development of the transboundary module of EUCalc. This workshop

was an important milestone in the research and design of the transboundary module, as

the discussions at the workshop resulted in many important and insightful suggestions that

will guide the development of the transboundary module. We plan to continue to engage

the experts, those who attended the workshop as well as those who, although unable to

attend the workshop, expressed their interest to be involved.

The workshop participants recognize the uniqueness of the EUCalc modeling approach and

its potential contributions to the EU decarbonization debates. The major challenges

associated with modeling the transboundary effects among the EU MS and between the EU

and the ROW using "bottom-up" inputs from the rest of the EUCalc model, as presented at

the workshop, are clearly understood by the participants. The discussions centered around

three sets of questions distributed in the pre-reading material in advance have yielded

many fruitful discussions. Some of these discussions point to useful recommendations and

suggestions for the further modeling work in the transboundary effect module, whereas

other discussions further reveal the complex nature of the modeling choices that the

EUCalc team has to make in the modeling work.

Regarding the first set of the questions on representative scenarios to be formulated and

simulated in the transboundary effect module, the experts agree with the team's general

approach to only select and model relevant and representative EUCalc scenarios. On the

three sets of scenarios that we proposed in the pre-reading material, the experts

emphasized the need to pay attention to the scenarios that are likely to be used by users.

One suggestion is to aggregate along the member state dimension and focus more on

sectoral decarbonization differences. This effectively further reduces the number of

scenarios to be modeled. Another suggestion is to model an even smaller set of scenarios

and list them as pre-defined pathways in the EUCalc pathway explorer. In general, the

experts cautioned against the ambition to model too many scenarios in a complex CGE

economic model. The ideas of using the selected representative scenarios to "envelope"

or representing the full set of EUCalc pathways are supported by the participants; however,

the experts were quite cautious about the necessity and the feasibility to make

"interpolations" to approximate the non-modeled scenarios.

On the second set of the questions regarding the exploitation of the results, the participants

offered insightful suggestions and recommendations. They agreed with the need to further

process the transboundary results into key indicators to facilitate the display of such

results. Among the suggested indicators are the ones that can be derived from the

modeling results, such as overall changes in trade balances and carbon leakages through

trade by country and at EU level, and such indicators broken down by key sectors. Other

suggested indicators were also mentioned, such as air pollutants and labor market related

issues, which are out of the scope of the transboundary module but are dealt with in other

EUCalc modules. Other suggestions are also mentioned on how to provide interactive

menus on the pathway explorer to allow users to dig deeper into the results – a suggestion

that will be investigated further.

The last set of the questions deals with both the macro level development of trade and

globalization and the underlying modeling instruments of these macro trends, as reflected

in the design of the baseline and the selected scenarios. Here, there is a broad support for

the baseline compilation and implementation approach documented in D7.1. On the

D7.3

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specific modeling issues that we brought for discussion at the workshop (e.g. long term

trade policy trends, trade to GDP ratio, size of trade elasticities, sectoral productivity

growth, oil prices, and land supply), it appears that modelers generally agree to a set of

"best practices" (which are in fact being used by the EUCalc team) while recognizing the

fact that the exact model implementations do differ across models and modeling teams.

The specific suggestions gathered in this session pointed us to additional data, parameters

and assumptions that will either be used or cited as further references in the modeling

work.

D7.3

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5 References

AGUIAR, A., NARAYANAN, B. & MCDOUGALL, R. 2016. An Overview of the GTAP 9 Data Base. Journal of Global Economic Analysis; Vol 1, No 1 (2016), 1,

181-208.

BAUDRY, G., CLORA, F., MWABONJE, O., THURM, B., WOODS, J. & YU, W. 2018.

DOcumentation of GTAP-EUCalc interface and design of GTAP scenarios. EUCAlc Deliverable 7.2.

BEKKERS, E., FRANCOIS, J. F. & ROJAS-ROMAGOSA, H. 2018. Melting Ice Caps

and the Economic Impact of Opening the Northern Sea Route. The Economic Journal, 128, 1095-1127.

BURFISHER, M. E. 2011. Introduction to Computable General Equilibrium Models, Cambridge, Cambridge University Press.

BURNIAUX, J.-M. & TRUONG, T. 2002. GTAP-E: An Energy-Environmental

Version of the GTAP Model. Department of Agricultural Economics, Purdue University, West Lafayette, IN: Global Trade Analysis Project (GTAP).

CHEPELIEV, M., MCDOUGALL, R. & VAN DER MENSBRUGGHE, D. 2018. Including Fossil-fuel Consumption Subsidies in the GTAP Data Base. 2018, 3, 38.

DELLINK, R., CHATEAU, J., LANZI, E. & MAGNÉ, B. 2017. Long-term economic

growth projections in the Shared Socioeconomic Pathways. Global Environmental Change, 42, 200-214.

DIXON, P. B. & RIMMER, M. T. 2002. Dynamic general equilibrium modelling for forecasting and policy : a practical guide and documentation of Monash,

Amsterdam : Elsevier.

EUROPEAN COMMISSION 2008. Communication from the Commission to the European Parliament, the Council, the European Economic and Social

Committee and the Committee of the Regions - 20 20 by 2020 - Europe's climate change opportunity. COM(2008) 30 final, COM(2008) 30 final.

EUROPEAN COMMISSION 2011. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. A Roadmap for moving to a

competitive low carbon economy in 2050. COM/2011/0112 final, COM/2011/0112 final.

EUROPEAN COMMISSION, DG ENERGY, DG CLIMATE ACTION & DG MOBILITY AND TRANSPORT 2016. EU Reference Scenario 2016. Energy, transport and GHG emissions Trends to 2050.

EUROPEAN COMMISSION (DG ECFIN) & ECONOMIC POLICY COMMITTEE (AWG) 2014. The 2015 Ageing Report Underlying Assumptions and Projection

Methodologies. European Economy Report No. 8.

EUROPEAN COMMISSION (DG ECFIN) & ECONOMIC POLICY COMMITTEE (AWG) 2015. The 2015 Ageing Report Economic and budgetary projections for the

28 EU Member States (2013-2060. European Economy Report No. 3.

D7.3

21

FOURÉ, J. & FONTAGNÉ, L. 2016. Long term socio-economic scenarios for Representative Concentration Pathways defining alternative CO2 emission

trajectories. CEPII Research Report, 1.

FOURÉ, J. & FONTAGNÉ, L. 2018. CALIBRATING LONG-TERM TRADE BASELINES IN GENERAL EQUILIBRIUM. Department of Agricultural Economics, Purdue

University, West Lafayette, IN: Global Trade Analysis Project (GTAP).

FRANCOIS, J. & MCDONALD, B. 1996. Liberalization and Capital Accumulation in

the GTAP Model. Department of Agricultural Economics, Purdue University, West Lafayette, IN: Global Trade Analysis Project (GTAP).

HERRENDORF, B., ROGERSON, R. & VALENTINYI, Á. 2014. Chapter 6 - Growth

and Structural Transformation. In: AGHION, P. & DURLAUF, S. N. (eds.) Handbook of Economic Growth. Elsevier.

HERTEL, T., POWELL, A., FRISVOLD, G., GEHLHAR, M., GRAY, D., HANSLOW, K., HUFF, K., IANCHOVICHINA, E., KUHN, B., LANCLOS, D. K., MACLAREN, D., MARTIN, W., MCDONALD, B., MCDOUGALL, R., PEARSON, K., PERRONI,

C., SWAMINATHAN, P., TSIGAS, M., TYERS, R., WIGLE, R., YANG, Y., YANAGISHIMA, K. & YOUNG, L. M. 1997. Global Trade Analysis: Modeling

and Applications, Department of Agricultural Economics, Purdue University, West Lafayette, IN, Global Trade Analysis Project (GTAP).

HUKKINEN, J., GÄCHTER, M., FERRARA, L., DIMITROPOULOU, D., KEENEY, M.,

LODGE, D., DERVIZ, A., BUSSIÈRE, M., CEZAR, R. & MROCZEK, W. 2016. Understanding the weakness in global trade-What is the new normal? :

European Central Bank.

IEA 2012. World Energy Outlook 2012.

IEA 2017. Energy Technology Perspectives 2017.

KAYA, Y. & YOKOBURI, K. 1997. Environment, energy, and economy : strategies for sustainability, Tokyo United Nations Univ. Press.

KC, S. & LUTZ, W. 2017. The human core of the shared socioeconomic pathways: Population scenarios by age, sex and level of education for all

countries to 2100. Global Environmental Change, 42, 181-192.

MCDOUGALL, R. & GOLUB, A. 2007. GTAP-E: A Revised Energy-Environmental Version of the GTAP Model. Department of Agricultural Economics, Purdue

University, West Lafayette, IN: Global Trade Analysis Project (GTAP).

OECD & WTO 2015. Aid for Trade at a Glance 2015: Reducing Trade Costs for

Inclusive, Sustainable Growth.

PHILIPPIDIS, G., HELMING, J. & TAEBEAU, A. 2017. Land Supply Elasticities. In: UNION, P. O. O. T. E. (ed.) JRC Technical Reports.

RENWICK, A., JANSSON, T., VERBURG, P. H., REVOREDO-GIHA, C., BRITZ, W., GOCHT, A. & MCCRACKEN, D. 2013. Policy reform and agricultural land

abandonment in the EU. Land Use Policy, 30, 446-457.

ROBINSON, S., MEIJL, H., WILLENBOCKEL, D., VALIN, H., FUJIMORI, S., MASUI, T., SANDS, R., WISE, M., CALVIN, K., HAVLIK, P., MASON D'CROZ, D.,

TABEAU, A., KAVALLARI, A., SCHMITZ, C., DIETRICH, J. P. & LAMPE, M. 2014. Comparing supply-side specifications in models of global agriculture

and the food system. Agricultural Economics, 45, 21-35.

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SCHUERENBERG-FROSCH, H. 2015. We couldn't care less about Armington elasticities - but should we? A systematic analysis of the influence of

Armington elasticity misspecification on model results. Department of Agricultural Economics, Purdue University, West Lafayette, IN: Global Trade Analysis Project (GTAP).

VAN DER MENSBRUGGHE, D. 2005. Linkage technical reference document. Development Prospects Group, The World Bank.

VAN DER MENSBRUGGHE, D. 2018. The environmental impact and sustainability applied general equilibrium (ENVISAGE) model, Version 10.01. Center for Global Trade Analysis, Purdue University.

WING, I. S. 2004. Computable general equilibrium models and their use in economy-wide policy analysis. Technical Note, Joint Program on the

Science and Policy of Global Change, MIT.

WTO 2018a. World Trade Report 2018 - The future of world trade: How divital technologies are transforming global commerce.

WTO 2018b. World Trade Statistical Review 2018.

YU, W. & CLORA, F. 2018. Formulation of baseline projections and

documentation on modeling approach review. EUCalc Deliverable 7.1.

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6 Annexes

6.1 Participants list

Participants – Stakeholders:

First Name Last Name Organization

Klaus Mittenzwei NIBIO (Norwegian Institute of Bioeconomy Research)

Eddy Bekkers WTO (World Trade Organization)

Jean Fouré CEPII (Centre d'étudesprospectives et

d'informationsinternationales), Paris

Maksym Chepeliev GTAP (Center for Global Trade Analysis, Purdue

University)

Alessandro Antimiani European Commission

Carsten Wachholz EIB (European Investment Bank)

Abderrahim Assab EBRD (European Bank for Reconstruction and

Development)

Stephan Zimmermann World Bank / GFDRR

Marcel Adenauer OECD

David Lopez ECF (European Climate Foundation)

Remotely

Hugo Valin IIASA

Participants – European Calculator:

First Name Last Name Organization

Wusheng Yu University of Copenhagen

Francesco Clora University of Copenhagen

Jeremy Woods Imperial College London

Tsan Wang TU Delft

Judit Kockat BPIE (Buildings Performance Institute Europe)

Ana Rankovic SEE Change Network

Facilitator:

First Name Last Name Organization

Adrian Taylor 4sing

D7.3

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6.2 Workshop agenda

Thursday, November 22, 2018 from 10:30 AM to 5:30 PM CET

European Climate Foundation (ECF) Building, 1040 Brussels

Time Activity

10:00 – 10.30 Coffee/tea and registration

10.30 – 10:45

Opening & welcome - Workshop agenda, objectives, participants

introduction

Prof. Wusheng Yu, University of Copenhagen

Adrian Taylor, 4sing (facilitator)

10:45-11:10

Presentation of the EUCalc project- Short overview presentation followed

by clarifying questions and brief discussion

Prof. Jeremy Woods, Imperial College London

Ana Rankovic, SEE Change Net

11:10 – 11:30

Background to Transboundary module of the EUCalc- Short overview

presentation on the methodology and assumptions

Prof. Wusheng Yu, University of Copenhagen

11:30 – 12:45

Interactive dialogue #1- exploring the most important, relevant and

representative user-defined pathways to be simulated in the EUCalc for

generating the transboundary effects

12:45 – 13:45 Lunch

13:45 – 15:00

Interactive dialogue #2 - discussing possible modalities for the

transboundary effects to be presented in the EUCalc (e.g. as trade matrix

itself or in terms of key indicators)

15:00 – 15:30 Coffee/tea

15.30 – 17.15

Interactive dialogue #3 - reflecting on the long run relationship between

GDP growth and trade expansion, the size of key parameters such as trade

elasticities (e.g. Armington elasticities), the use of differential sectoral

productivity growth pattern to generate expected structural changes, the

treatment of land and other natural resource supply, and the representation

of changing energy technologies in a trade-focused CGE model. Other issues

to be discussed include recent setbacks in globalization and global

cooperation, their implications on long run trade development and

decarbonization efforts, as well as the EU's future position and role in global

trade and global decarbonization efforts.

17:15 - 17:30 Wrap up and closing - Summary, key takeaways and next steps

http://www.european-calculator.eu/

D7.3

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6.3 Dialogues’ sheet

Topic #1 Exploring the most important,

relevant and representative user-defined pathways to be simulated in the EUCalc for generating the transboundary effects

Questions:

A. What are the most important, relevant and representative user-defined EUCalc pathways/scenarios to be simulated for generating the transboundary effects to be included in EUCalc? B. Are the three sets of scenarios mentioned below the important/relevant ones, and if so, are we too ambitious in planning on simulating all these scenarios?

C. Are there other important/relevant scenarios that are not included in the three sets of scenarios mentioned below? There are three sets of scenarios anticipated:

1. Scenarios with identical ambition levels in all sectors and countries;

2. Scenarios with different ambitions across the sectors, with sectoral ambition levels being kept the same across EU MS;

3. Scenarios with deviations by individual countries from the EU-wide ambition, i.e. each EU MS is assumed to deviate its level settings (uniform across sectors) from the common level setting assumed for all other MS in the core scenario.

Topic #2 Ways to present transboundary effects in the EUCalc (e.g. as the

trade matrix itself or in terms of key indicators)

Questions:

i) What key transboundary effects (e.g. intra and extra-EU trade flows) should the model focus on?

ii) At what sectoral aggregation level (i.e. no sector breakdown - the economy as a whole - or broadly defined

sectors such as agriculture, manufacturing, services and the energy sectors, or more detailed sectors actually represented in the model) and for which key sectors should results be presented?

iii) How should the transboundary effects be presented in EUCalc (e.g. as the trade matrix itself or in terms of key indicators such as self-sufficiency ratio, trade dependency/exposure index, revealed comparative advantage index, etc.)?

D7.3

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Topic #3a Reflecting on the long run relationship between GDP growth

and trade expansion, the size of key parameters such as trade elasticities (e.g. Armington elasticities), the use of differential sectoral productivity growth

pattern to generate expected structural changes, the treatment

of land and other natural resource supply, and the representation of changing energy technologies in a trade-focused CGE model.

Questions:

i) In the baseline projection, what guidance can you give on adopting appropriate trade elasticities given the expected major structural changes in the world economy?

ii) What approach should be taken on modelling differential sectoral productivity growth?

iii) Assumptions regarding the trade-to-income elasticity are essential. However, this elasticity appears to have been falling in recent years relative to its long-run trend. So, should we assume a linear, or a changing link between GDP growth and trade expansion? How can we mimic this relationship in the baseline projection?

iv) Regarding the treatment of long-run supply of land, would it be reasonable to assume a simple land supply function? If so, what is the appropriate size of the land supply elasticity? To model the long run supply of natural resources, would it be sufficient to target a set of natural resource prices (e.g. crude oil and

natural gas prices)?

Topic #3b Issues to be discussed include recent setbacks in globalization and global cooperation, their implications on

long run trade development and decarbonization efforts, as well as the EU's future position and role in

global trade and global decarbonization efforts.

Questions:

i) Regarding trade policy trends, are recent setbacks in globalization and global cooperation merely a transitory phenomenon or will they be the persistent norm, and how do these trends impact long-run trade development

and decarbonization efforts?

ii) What impact will trade policy trends have on the EU's future position and role in global trade and global decarbonization efforts?

iii) Are we expecting a different relationship between GDP growth and trade expansion in the next three

decades, as compared to the experience in the last several decades when trade expansion has generally outpaced GDP growth?